Am I crazy

to start teaching my class Introduction to Machine Learning, with the above slide? Also, am I crazy to use the above image as a plug for the course which is about to start?

To be sure, topics like statistics and probability can induce math anxiety. And not to mention abject boredom! But here's the good news: You don't need to be a math wizard to grasp concepts such as the Bayes Theorem (and classifier) depicted above. And not merely grasp, but relish, enjoy and apply.

Prospective students might be wondering,

"Why should I bother with Bayes Theorem when I can just ask an LLM to design a model for me?"

Good point! In fact, I encourage students to use ChatGPT to "solve" the assignments in this course. And then I challenge them with some very simple questions about their solution. How do you think they respond? I can tell you that they experience boundless joy when they finally grasp the real meaning of the assignment.

As already pointed out by astute practitioners in this very medium, relying solely on Large Language Models (LLMs) like ChatGPT for designing machine learning models is not just a shortcut—it's a professional hazard. In the rapidly evolving field of machine learning, those who fail to understand the fundamentals will be left behind. LLMs can assist (as it did in providing a very rough draft of this article), but at the time this article is being written, they cannot replace the need for deep, critical thinking. Here is an uncomfortable, if well-known, truth: LLMs often provide a superficial understanding and can lead you down a path of over-reliance and intellectual complacency.

Undoubtedly, there is a time and place to employ LLMs. Read my daughter's article Digital Delicacies: When AI Gets Hungry. But note that in countless cases, simple Bayesian models can outperform more complex models designed by LLMs, especially when data is sparse or imbalanced. For example, in fraud detection, a Bayesian approach can continuously update the likelihood of fraudulent activity as new data -- which might either be quantitative or qualitative -- comes in, leading to more accurate and timely predictions.

By understanding foundational concepts like Bayes Theorem, you'll develop the critical thinking skills needed to evaluate and improve models, rather than just accepting whatever an LLM generates. Let’s embark on this challenging, rewarding, and absolutely necessary journey together. Your future self will thank you.